Methods and systems for processing time-series well data using higher order channels to identify features therein and alter hydraulic fracturing operations based thereon
Abstract
A method for identifying characteristics of well data comprises receiving hydraulic fracturing data comprising data channels from a stage or stages of a hydraulic fracturing sequence and preprocessing the data channel, which may include normalizing and recalibrating the hydraulic fracturing data. The method further involves generating one or more additional higher order channels based on the normalized and recalibrated hydraulic fracturing data, the one or more additional channels derived at least in part from parameters of the normalized and recalibrated hydraulic fracturing data. The system may combine the higher order channels with the accessed data channels, and further process, combine and otherwise identify hydraulic fracturing events at the well being hydraulically fractured based on the received hydraulic fracturing data and the one or more additional channels. From the identified events, the system may alter hydraulically fracturing attributes of a stage being completed and/or subsequent stages of the well or subsequent wells.
Claims
exact text as granted — not AI-modifiedWhat we claim:
1. A non-transitory computer readable medium comprising computer executable instructions that, when executed by a processor, cause the processor to:
access a bottomhole proppant concentration data channel comprising a series of bottomhole proppant concentration values for a stage being hydraulically fractured;
normalize the bottomhole proppant concentration data channel to yield a normalized bottomhole proppant concentration data channel;
quantize the normalized bottomhole proppant concentration data channel to yield a quantized bottomhole proppant concentration data channel and to generate a proppant ramp data channel denoting at least one time period encompassing at least one proppant ramp where the quantized bottomhole proppant concentration data channel meets a first threshold value, the at least one time period representing the at least one proppant ramp;
generate a slurry volume data channel from a slurry rate data channel temporally aligned with at least a portion of the bottomhole proppant concentration data channel, the slurry volume data channel providing a cumulative slurry volume data over time;
for a time preceding a first one of the at least one time period representing the at least one proppant ramp, identifying when a slurry volume resides in a range and a maximum bottomhole proppant concentration is at least a specific value to identify an acid pulse; and
identify a hydraulic fracturing event based on when the slurry volume resides in the range and the maximum bottomhole proppant concentration is at least the specific value.
2. The non-transitory computer readable medium of claim 1 , the computer executable instructions further causing the processor to:
delete any denoted at least one time period representing the at least one proppant ramp when the at least one time period does not meet a second threshold value; and
generate information from the proppant ramp data channel.
3. A method of identifying hydraulic fracturing events from time-series data comprising:
accessing, with a processor, a bottomhole proppant concentration data channel comprising a series of bottomhole proppant concentration values for a stage being hydraulically fractured;
normalizing the bottomhole proppant concentration data channel to yield a normalized bottomhole proppant concentration data channel;
quantizing the normalized bottomhole proppant concentration data channel to yield a quantized bottomhole proppant concentration data channel and to generate a proppant ramp data channel denoting at least one time period encompassing at least one proppant ramp where the quantized bottomhole proppant concentration data channel meets a first threshold value, the at least one time period representing the at least one proppant ramp;
generating a slurry volume data channel from a slurry rate data channel temporally aligned with at least a portion of the bottomhole proppant concentration data channel, the slurry volume data channel providing a cumulative slurry volume data over time; and
identify a hydraulic fracturing event based on the slurry volume data channel and the proppant ramp data channel.
4. The method of claim 3 wherein the first threshold value is greater than zero.
5. The method of claim 3 further comprising deleting any denoted at least one time period representing the at least one proppant ramp when the at least one time period does not meet a second threshold value.
6. The method of claim 5 wherein the second threshold value is 600 seconds.
7. The method of claim 3 further comprising combining the proppant ramp data channel with at least one additional data channel for the stage being hydraulically fractured, and generating information from the proppant ramp data channel and the at least one additional data channel for the at least one proppant ramp.
8. The method of claim 3 further comprising:
identifying a first one of the at least one time period representing the at least one proppant ramp; and
identifying a time of a beginning of the first one of the at least one time period representing the at least one proppant ramp.
9. The method of claim 8 , further comprising, for a time preceding the first one of the at least one time period representing the at least one proppant ramp, identifying when a slurry volume resides in a range and a maximum bottomhole proppant concentration is at least a specific value to identify an acid pulse.
10. The method of claim 9 further comprising identifying the acid pulse based on a highest value of the highest bottomhole proppant concentration.
11. A non-transitory computer readable medium comprising computer executable instructions that, when executed by a processor, cause the processor to perform:
receive hydraulic fracturing data comprising at least one data channel for at least one stage of a hydraulic fracturing sequence, the hydraulic fracturing data being a slurry rate for a stage being hydraulically fractured;
preprocess the at least one data channel to yield preprocessed hydraulic fracturing data;
generate one or more additional data channels based on the preprocessed hydraulic fracturing data, the one or more additional data channels being a slurry volume data channel for the stage being hydraulically fractured; and
generate the slurry volume data channel from a slurry rate data channel temporally aligned with at least a portion of a bottomhole proppant concentration data channel, the slurry volume data channel providing a cumulative slurry volume data over time; and
identify a hydraulic fracturing event based on the hydraulic fracturing data and the one or more additional data channels, the hydraulic fracturing event being a target slurry rate.
12. The non-transitory computer readable medium of claim 11 , the computer executable instructions further the processor to:
apply a transform function to an interpolated slurry rate signal based on the slurry rate and the slurry volume data channel, the transform function identifying a peak that correlates with a time when the target slurry rate is reached.
13. The non-transitory computer readable medium of claim 11 , the computer executable instructions further cause the processor to:
generate a cumulative proppant data channel and a bottomhole cumulative proppant data channel; and
generate a cross correlation and identify a peak of the cross correlation, a volume corresponding to the peak being identified as a flush volume.Cited by (0)
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